We need to roughly estimate the Medicare demand for beds, as an addition to traditional long-term care demand, to correctly determine whether the local demand for skilled nursing is satisfied. To that end, consider the following approach: taking 1.2% of the local 75 and over population.[c], (75 or older) was 19,741,663. Taking fully-occupied short-stay beds as a proportion of the 75 and older population gives 0.94% (186,298 / 19,741,663); 0.94% of the 75+ population will be utilizing a Medicare-covered bed, on average, each day. However, given time taken to turn-over beds, process new patients, and allowing for peak demand, we would expect less than full occupancy in each facility, thereby requiring additional licensed beds:
BEDS BY STABILIZED OCCUPANCY
Given that a number between 70 and 80 percent reflects a rough average of observed occupancy, as well as a frequently chosen target for Pro-forma calculations in short-stay projects, we see using a 1.2% ratio of the local 75 and over population (near the upper end of the occupancy range) as a reasonable proxy for short-stay Medicare demand. This number is of course a rough estimate, and qualitative factors at the local level will affect local demand:
- If a particular area is a target for medical travel (perhaps located close to a county, state, or national border; or, containing a particular medical specialty), we would expect higher than normal demand as patients recuperate near the hospital rather than near home.
- If the local ratio of 65-74 year olds to those 75 and older is greatly different than the national ratio, 75 and over population may no longer be as accurate a proxy.
- If there are no (or too few) nearby hospitals, perhaps as a result of recent population growth, there may not be enough hospital stays to discharge from in the local area, resulting in lower than normal local demand (ie, these are the travelers in point 1).
- Quality of available care, adoption of preventative care, SNF/Medicare alternatives, location of family, legal or legislative changes, etc., will all similarly affect the local demand.
[b] As this reflects data from 2013, it does not factor in any recently (2014-2017) proposed legislation, or the upcoming GOP-led healthcare changes.